Data Scientist

Our culture lifts you up—there is no ego in the way. Our common purpose? We all want to win for our customers. We aim to always be evolving, dynamic, and ambitious. We believe in the power of genuine connections. Each employee is a part of what makes us unique on the market: agile and dedicated.

Time Type:

Regular

Job Description :

Data Scientist

Position Summary:

We are looking for a skilled and motivated Data Scientist to join Cogeco’s Data Science and Analytics practice. In this role, you will play a key part in developing and implementing data models and strategies to improve customer acquisition, retention, and overall business performance. You will work closely with cross-functional teams to identify opportunities, develop advanced analytics, and deploy machine learning models that directly impact commercial growth and customer experience.

The Data Scientist applies expertise in artificial intelligence through use of machine learning, data mining, and information retrieval to design, prototype and build next generation advanced analytics engines and services. The data scientist collaborates with business partners to define the technical problem statement and hypothesis to test; develops efficient and accurate analytical models that inform business decisions, and incorporates them into analytical data products or tools with the support of a cross-functional team.

Responsibilities:

• As a Data Scientist at Cogeco, you will develop predictive modeling and machine learning solutions to complex business problems creating value for the business.

• Transform data into insights that help to improve the value of the business

• Execute exploratory data analysis, data preprocessing, model development, model deployment and monitoring.

• Utilize machine learning techniques to improve customer segmentation, churn prediction, and personalized marketing efforts.

• Plan and execute analytical experiments to help solve business problems

• Propose solutions and strategies to business challenges

• Continuously refine and improve models based on feedback and changing business needs.

• Leverage advanced analytics techniques to develop deep knowledge of the customer experience, use data and analytics to optimize marketing campaigns, and develop strategies through insights to attract new customers and retain existing ones.

• Collaborate with business partners to develop novel ways to meet objectives utilizing cutting edge techniques and tools.

• Effectively communicate the analytics approach and data science lifecycle with leadership and business partners.

• Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems

• Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers

• Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products

• Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources

• Share your passion for Data Science with broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards

• Collaborate, coach, and learn with a growing team of experienced Data Scientists

Qualifications:

• Bachelor’s degree required, MS or PhD preferred.

• Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 5+ years experience required OR Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 2+ years work experience.

• Must have proficiency writing complex SQL queries.

• Advanced hands-on experience with the Python data science stack.

• Track record of analytical projects covering all stages of the data science lifecycle.

• Strong understanding of quantitative approaches, their benefits, and their limitations.

• Analytical ability required to gather data, perform transformation, perform complex analysis, solve both business and technical problems.

• Proficiency with data mining, mathematics, and statistical analysis.

• Experience in pattern reco